ESTRATÉGIAS DE LEITURA / STRATEGIES OF READING

O presente artigo discorre sobre a importância da utilização de estratégias de ensino/aprendizagem de leitura dentro de sala de aula. Através de uma pesquisa bibliográfica, propõe-se compreender a relevância de ações sistematizadas e organizadas de ensino de leitura, visando sua contribuição no processo de aquisição do hábito de ler. A discussão está situada no âmbito da Teria Interacionista de Leitura. Espera-se que o presente trabalho possa servir, não somente como reflexão para trabalhos posteriores, mas sirva de estímulo à inserção das estratégias e procedimentos na prática dos docentes que a ele tiverem acesso e que, de certa forma, funcione como uma espécie de “colírio” teórico-metodológico que amplie a perspectiva sobre a real necessidade de reformulação de muitas práticas de ensino de leitura

Use of threshold electrolyte concentration analysis to determine salinity and sodicity limit of irrigation water

This research studied threshold electrolyte concentration (TEC) of irrigation water and its effect on the infiltration rate of two contrasting soils from Pernambuco state, Brazil. The experiment was conducted in the Soil Chemistry and Salinity Laboratory of Federal Rural University of Pernambuco. Each soil was packed in five Buchner funnels, where one funnel from each soil was submitted to treatment with solution of electrical conductivity (EC) of 0.5, 1.0, 2.0, 4.0 or 8.0 dS m-1. For each funnel containing soil, an increasing ratio of NaCl to CaCl2 was applied in a treatment solution to achieve 10 increasing values of sodium adsorption ratio (SAR) from 0 to 100. These solutions were applied through a Mariotte bottle, with a constant hydraulic head of ~2 cm (pressure potential). After a liter of solution had drained, in the flux was collected for a known time interval, until steady state was reached. Darcy's equation was used to calculate saturated hydraulic conductivity (Ksat) and a mathematical model used to calculate the TEC as a 20% reduction in Ksat. By increasing SAR similar behavior was noted between the two soils, whereby Ksat decreased, although the relative decrease in Ksat was greater for SAR of 100 in the soil with higher clay content

Effects of high intensity interval training on neuro-cardiovascular dynamic changes and mitochondrial dysfunction induced by high-fat diet in rats

This research was supported by the Brazilian National Council for Scientific and Technologic Development (CNPq) (Grant number: 474116/2008-5) and Carlos Chagas Filho Foundation for Research Support in the State of Rio de Janeiro (FAPERJ) (Grant number: E-26/ 111.732/2011), both received by Eliete Bouskela. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Rarity of monodominance in hyperdiverse Amazonian forests.

Tropical forests are known for their high diversity. Yet, forest patches do occur in the tropics where a single tree species is dominant. Such "monodominant" forests are known from all of the main tropical regions. For Amazonia, we sampled the occurrence of monodominance in a massive, basin-wide database of forest-inventory plots from the Amazon Tree Diversity Network (ATDN). Utilizing a simple defining metric of at least half of the trees ≥ 10 cm diameter belonging to one species, we found only a few occurrences of monodominance in Amazonia, and the phenomenon was not significantly linked to previously hypothesized life history traits such wood density, seed mass, ectomycorrhizal associations, or Rhizobium nodulation. In our analysis, coppicing (the formation of sprouts at the base of the tree or on roots) was the only trait significantly linked to monodominance. While at specific locales coppicing or ectomycorrhizal associations may confer a considerable advantage to a tree species and lead to its monodominance, very few species have these traits. Mining of the ATDN dataset suggests that monodominance is quite rare in Amazonia, and may be linked primarily to edaphic factors

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio